General redundancy optimization method for cooperating manipulators using quadratic inequality constraints

1999 ◽  
Vol 29 (1) ◽  
pp. 41-51 ◽  
Author(s):  
Woong Kwon ◽  
Beom Hee Lee
Keyword(s):  
Inequality Constraints ◽  
Optimization Method ◽  
Quadratic Inequality ◽  
Cooperating Manipulators ◽  
Quadratic Inequality Constraints ◽  
Redundancy Optimization

scholarly journals Set-Membership Filtering for Nonlinear Dynamic Systems With Quadratic Inequality Constraints

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 13375-13386
Author(s):  
Xiaowei Li ◽  
Xuedong Yuan ◽  
Fanqin Meng ◽  
Yiwei Liao ◽  
Haiqi Liu ◽  
...  
Keyword(s):  
Dynamic Systems ◽  
Nonlinear Dynamic ◽  
Inequality Constraints ◽  
Nonlinear Dynamic Systems ◽  
Quadratic Inequality ◽  
Set Membership ◽  
Quadratic Inequality Constraints

Resolving kinematic redundancy of a robot using a quadratically constrained optimization technique

Robotica ◽  
1999 ◽  
Vol 17 (5) ◽  
pp. 503-511 ◽  
Author(s):  
Woong Kwon ◽  
Beom Hee Lee ◽  
Myoung Hwan Choi
Keyword(s):  
Constrained Optimization ◽  
Optimization Technique ◽  
Inequality Constraints ◽  
Redundancy Resolution ◽  
Kinematic Redundancy ◽  
Problem Size ◽  
Physical Constraints ◽  
Quadratic Inequality ◽  
Quadratic Inequality Constraints ◽  
Quadratically Constrained

The constraints on the physical limit should be considered in a kinematic redundancy resolution problem of a robot. This paper proposes a new optimization scheme to resolve kinematic redundancy of the robot while considering physical constraints. In the proposed scheme, quadratic inequality constraints are used in place of linear inequality constraints, thus a quadratically constrained optimization technique is applied to resolve the redundancy. It is shown that the use of quadratic inequality constraints considerably reduces the number of constraints. Therefore, the proposed method reduces the problem size considerably and makes the problem simple resulting in computational efficiency. A numerical example of a 4-link planar redundant robot is included to demonstrate the efficiency of the proposed optimization technique. In this example, simulation results using the proposed method and another well-known method are compared and discussed.

scholarly journals Optimization for energy consumption in drying section of fluting paper machine

2017 ◽  
Vol 21 (3) ◽  
pp. 1419-1429
Author(s):  
Shaaban Ghodbanan ◽  
Reza Alizadeh ◽  
Sirous Shafiei
Keyword(s):  
Process Parameters ◽  
Heat Recovery ◽  
Production Capacity ◽  
Inequality Constraints ◽  
Optimization Method ◽  
Energy Performance ◽  
Operating Conditions ◽  
Paper Machine ◽  
Recovery Performance ◽  
Drying Section

Non-linear programming optimization method was used to optimize total steam and air consumption in the dryer section of multi-cylinder fluting paper machine. Equality constraints of the optimization model were obtained from specified process blocks considering mass and energy balance relationships in drying and heat recovery sections. Inequality constraints correspond to process parameters such as production capacity, operating conditions, and other limitations. Using the simulation, the process parameters can be optimized to improve the energy efficiency and heat recovery performance. For a corrugating machine, optimized parameters show the total steam use can be reduced by about 11% due to improvement of the heat recovery performance and optimization of the operating conditions such as inlet web dryness, evaporation rate, and exhaust air humidity, accordingly total steam consumption can be decreased from about 1.71 to 1.53 tonnes steam per tonne paper production. The humidity of the exhaust air should be kept as high as possible to optimize the energy performance and avoid condensation in the pocket dryers and hood exhaust air. So the simulation shows the supply air should be increased by about 10% to achieve optimal humidity level which was determined about 0.152 kgH2O/(kg dry air).

Mode Shape Expansion Techniques for Model Error Localization and Damage Detection

1995 ◽  
Author(s):  
Marie B. Levine-West ◽  
Mark H. Milman
Keyword(s):  
Mode Shape ◽  
Optimization Problems ◽  
Inequality Constraints ◽  
Model Error ◽  
Analytical Models ◽  
Mode Shapes ◽  
Orthogonal Projections ◽  
Modal Expansion ◽  
Expansion Technique ◽  
Quadratic Inequality Constraints

Abstract Several methods for mode shape expansion are investigated. The most popular methods use the dynamic equations of motions to obtain direct solutions, or use orthogonal projections. Both approaches can also be formulated as constrained optimization problems. To account for uncertainties in the measurements and in the prediction, a new expansion technique based on least squares minimization with quadratic inequality constraints (LSQI) is proposed. Each modal expansion technique is evaluated with experimental data obtained on the Micro-Precision Interferometer testbed, using both the pre-test and updated analytical models. The robustness of these methods is verified with respect to measurement noise and model error. It is shown that the proposed LSQI method has the best performance and can reliably predict mode shapes, and can be used to locate damage elements, even in very adverse situations. A new LSQI algorithm is also proposed which significantly decreases the solution time.

Application of SCE-UA Approach to Economic Load Dispatch of Hydrothermal Generation System

2013 ◽  
Vol 448-453 ◽  
pp. 4296-4303
Author(s):  
Jia Rui Dong ◽  
Chui Yong Zheng ◽  
Guang Yuan Kan ◽  
Zhi Jia Li ◽  
Min Zhao
Keyword(s):  
Parameter Space ◽  
Inequality Constraints ◽  
Optimization Methods ◽  
Optimization Method ◽  
Global Optimum ◽  
Scheduling Problem ◽  
Short Term ◽  
Hydrothermal Scheduling ◽  
Transport Delay ◽  
Hydraulic Network

The practical hydrothermal system is highly complex and possesses nonlinear relationship of the problem variables, cascading nature of hydraulic network and water transport delay, which make the problem of finding global optimum difficult using standard optimization methods. This paper presents a new approach to the solution of optimal power generation to short-term hydrothermal scheduling problem, using shuffled complex evolution (SCE-UA) method. The proposed method introduces the new concept of competitive evolution and complex shuffling, which ensure that the information on the parameter space gained by each of individual complexes is shared throughout the entire population. This conducts an efficient search of the parameter space. In this study, the hydrothermal scheduling is formulated as an objective problem that maximizes the social welfare. Penalty function is proposed to handle the equality, inequality constraints especially active power balance constraint and ramp rate constraints. The simulation results reveal that SCE-UA effectively overcomes the premature phenomenon and improves the global convergence and optimization searching capability. It is a relatively consistent, effective and efficient optimization method in solving the short-term hydrothermal scheduling problem.

Sign in / Sign up

Export Citation Format

Share Document